Abstract
This paper describes the University of Maryland’s submission to the WMT 2019 Kazakh-English news translation task. We study the impact of transfer learning from another low-resource but related language. We experiment with different ways of encoding lexical units to maximize lexical overlap between the two language pairs, as well as back-translation and ensembling. The submitted system improves over a Kazakh-only baseline by +5.45 BLEU on newstest2019.- Anthology ID:
- W19-5308
- Volume:
- Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1)
- Month:
- August
- Year:
- 2019
- Address:
- Florence, Italy
- Editors:
- Ondřej Bojar, Rajen Chatterjee, Christian Federmann, Mark Fishel, Yvette Graham, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, André Martins, Christof Monz, Matteo Negri, Aurélie Névéol, Mariana Neves, Matt Post, Marco Turchi, Karin Verspoor
- Venue:
- WMT
- SIG:
- SIGMT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 134–140
- Language:
- URL:
- https://aclanthology.org/W19-5308
- DOI:
- 10.18653/v1/W19-5308
- Bibkey:
- Cite (ACL):
- Eleftheria Briakou and Marine Carpuat. 2019. The University of Maryland’s Kazakh-English Neural Machine Translation System at WMT19. In Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1), pages 134–140, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- The University of Maryland’s Kazakh-English Neural Machine Translation System at WMT19 (Briakou & Carpuat, WMT 2019)
- Copy Citation:
- PDF:
- https://aclanthology.org/W19-5308.pdf
Export citation
@inproceedings{briakou-carpuat-2019-university,
title = "The {U}niversity of {M}aryland{'}s {K}azakh-{E}nglish Neural Machine Translation System at {WMT}19",
author = "Briakou, Eleftheria and
Carpuat, Marine",
editor = "Bojar, Ond{\v{r}}ej and
Chatterjee, Rajen and
Federmann, Christian and
Fishel, Mark and
Graham, Yvette and
Haddow, Barry and
Huck, Matthias and
Yepes, Antonio Jimeno and
Koehn, Philipp and
Martins, Andr{\'e} and
Monz, Christof and
Negri, Matteo and
N{\'e}v{\'e}ol, Aur{\'e}lie and
Neves, Mariana and
Post, Matt and
Turchi, Marco and
Verspoor, Karin",
booktitle = "Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1)",
month = aug,
year = "2019",
address = "Florence, Italy",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W19-5308",
doi = "10.18653/v1/W19-5308",
pages = "134--140",
abstract = "This paper describes the University of Maryland{'}s submission to the WMT 2019 Kazakh-English news translation task. We study the impact of transfer learning from another low-resource but related language. We experiment with different ways of encoding lexical units to maximize lexical overlap between the two language pairs, as well as back-translation and ensembling. The submitted system improves over a Kazakh-only baseline by +5.45 BLEU on newstest2019.",
}
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%0 Conference Proceedings %T The University of Maryland’s Kazakh-English Neural Machine Translation System at WMT19 %A Briakou, Eleftheria %A Carpuat, Marine %Y Bojar, Ondřej %Y Chatterjee, Rajen %Y Federmann, Christian %Y Fishel, Mark %Y Graham, Yvette %Y Haddow, Barry %Y Huck, Matthias %Y Yepes, Antonio Jimeno %Y Koehn, Philipp %Y Martins, André %Y Monz, Christof %Y Negri, Matteo %Y Névéol, Aurélie %Y Neves, Mariana %Y Post, Matt %Y Turchi, Marco %Y Verspoor, Karin %S Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1) %D 2019 %8 August %I Association for Computational Linguistics %C Florence, Italy %F briakou-carpuat-2019-university %X This paper describes the University of Maryland’s submission to the WMT 2019 Kazakh-English news translation task. We study the impact of transfer learning from another low-resource but related language. We experiment with different ways of encoding lexical units to maximize lexical overlap between the two language pairs, as well as back-translation and ensembling. The submitted system improves over a Kazakh-only baseline by +5.45 BLEU on newstest2019. %R 10.18653/v1/W19-5308 %U https://aclanthology.org/W19-5308 %U https://doi.org/10.18653/v1/W19-5308 %P 134-140
Markdown (Informal)
[The University of Maryland’s Kazakh-English Neural Machine Translation System at WMT19](https://aclanthology.org/W19-5308) (Briakou & Carpuat, WMT 2019)
- The University of Maryland’s Kazakh-English Neural Machine Translation System at WMT19 (Briakou & Carpuat, WMT 2019)
ACL
- Eleftheria Briakou and Marine Carpuat. 2019. The University of Maryland’s Kazakh-English Neural Machine Translation System at WMT19. In Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1), pages 134–140, Florence, Italy. Association for Computational Linguistics.